aiInternal Project
Shopping Center Parking Lot Management
Computer vision system for parking lot management with 98% accuracy, featuring empty spot detection, license plate recognition, and car tracking.
Developed at ProManage
Lead Data Scientist
2020-2021
Internal project - no public access
Screenshots
About This Project
Created a comprehensive parking lot management system for shopping centers that uses computer vision to detect empty parking spots, recognize license plates using OCR, and track vehicles in real-time. The system provides an automated solution for efficient parking space utilization and vehicle management.
Key Features
- Real-time empty parking spot detection
- License plate recognition with OCR text extraction
- Vehicle tracking across camera feeds
- Occupancy statistics and heatmap visualization
- Automated entry/exit logging system
- Multi-camera feed processing and stitching
Challenges & Solutions
- Handling diverse lighting conditions (day, night, weather)
- Accurate license plate detection at various angles and distances
- Real-time processing of multiple camera feeds simultaneously
- Building robust OCR for different plate formats
Results & Impact
- 98% accuracy in parking lot detection and management
- Automated vehicle tracking and logging
- Improved parking utilization and customer experience
Technologies Used
PythonTensorFlowOpenCVOCRDeep LearningDocker
Project Details
- Category
- ai
- My Role
- Lead Data Scientist
- Duration
- 6 months
- Year
- 2020-2021
- Company
- ProManage
- Status
- Internal / Private
Internal Project
This project was developed for internal use at ProManage. Source code and live demo are not publicly available due to confidentiality.